Nyenhuis D L, Luchetta T, Yamamoto C, Terrien A, Bernardin L, Rao S M, Garron D C
Psychology Department, Rush-Presbyterian-St. Luke's Medical Center, Chicago, IL 60612, USA.
J Pers Assess. 1998 Apr;70(2):386-401. doi: 10.1207/s15327752jpa7002_14.
Current self-report depression scales may overestimate depression symptoms in medical patients by including items measuring symptoms inherent to many medical conditions. They may therefore reflect a patient's medical rather than psychological state. We present the Chicago Multiscale Depression Inventory (CMDI), a factorially derived self-report depression scale that includes Mood, Evaluative, and Vegetative subscales. The CMDI and its subscales were designed to be used separately or combined; we posit that the nonvegetative CMDI subscales are the most accurate means of examining depression in medical patients. In this study we outline the development, standardization, and initial validation of the CMDI, a multistep process that required a total sample of 1,062 adults. We show the CMDI and each of its subscales to be internally consistent, reliable, and valid. Confirmatory factor analysis supports the CMDI factor structure. Finally, we report standardization scores for each of the CMDI scales, derived from an age-, race- and gender-stratified standardization sample of 420 adults.
目前的自我报告抑郁量表可能会高估内科患者的抑郁症状，因为其中包含了许多内科疾病固有症状的测量项目。因此，这些量表可能反映的是患者的内科状况而非心理状态。我们推出了芝加哥多维度抑郁量表（CMDI），这是一个通过因素分析得出的自我报告抑郁量表，包括情绪、评估和植物神经子量表。CMDI及其子量表设计为可单独使用或组合使用；我们认为，非植物神经CMDI子量表是检查内科患者抑郁状况的最准确方法。在本研究中，我们概述了CMDI的开发、标准化和初步验证过程，这是一个多步骤过程，总共需要1062名成年人作为样本。我们证明CMDI及其每个子量表都具有内部一致性、可靠性和有效性。验证性因素分析支持CMDI的因素结构。最后，我们报告了CMDI各量表的标准化分数，这些分数来自420名成年人的年龄、种族和性别分层标准化样本。
